The present invention relates to automated machinery, and more specifically to an intelligent, automated diagnostic system for determining the cause of an error or fault in factory machines.
Complex factories are continuing to become more highly automated. More machines are used to perform the work of the factory, and each of these machines typically is becoming more complex.
The greatly increased complexity of automated and semi-automated factories provides many advantages. More highly automated factories are typically able to produce a higher volume and variety of products with better quality control. Thus, factories are expected to tend in the future toward higher levels of automation than currently exist.
One side effect of increasing complexity in the modern factory is the increasing difficulty of handling error conditions. The individual, highly complex machines used in many factories, such as fabrication and assembly facilities for integrated circuits, fail to a greater or lesser degree on a periodic basis. Many failures are not catastrophic in that the machine will continue to operate, although not within the desired parameters.
Products handled by out of tolerance machines may be rendered useless. Thus, the automated control systems for such machines generally contain a large number of sensors of the machine state. When some aspect of the machine goes out of tolerance, the control system can shut the machine down and raise an alarm for a human operator to intervene.
With very complex machinery, determining the cause of an error condition is not a trivial task. A given symptom may be caused by any of several independent failures, while a single failure can, depending on its precise nature, cause several different symptoms.
A human repair technician is required to fully check out a machine which has an error condition and make repairs as necessary. This can be an extremely time consuming process. Since so many process and machine variables interact in complex equipment, the repair technician is required to determine possible causes based on symptoms, determine proper operation of the appropriate parts of the machine in order to test his hypothesis, and effect repairs on malfunctioning items. As difficult as this task can be for even a highly trained technician operating on a single machine, the magnitude of the problem is compounded by the fact that dozens of different kinds of machines may be in operation on a single factory floor. Thus, a technician is required to be familiar with the operation and repair of many different machines.
The repair technician is faced with the further concern that some portion of the factory is shut down until repairs are complete. Since one of the characteristics of a highly automated factory is its high throughput of products, the down time required for repairs is especially problematical. This problem continues to worsen as factory machines continue to grow in number and complexity.
It would therefore be desirable to provide an automated diagnostic system which assists the repair technician with repairs of a machine in an error condition.